Fatigue dataset of high-entropy alloys

Abstract

Fatigue failure of metallic structures is of great concern to industrial applications. A material will not be practically useful if it is prone to fatigue failures. To take the advantage of lately emerged high-entropy alloys (HEAs) for designing novel fatigue-resistant alloys, we compiled a fatigue database of HEAs from the literature reported until the beginning of 2022. The database is subdivided into three categories, i.e., low-cycle fatigue (LCF), high-cycle fatigue (HCF), and fatigue crack growth rate (FCGR), which contain 15, 23, and 28 distinct data records, respectively. Each data record in any of three categories is characteristic of a summary, which is comprised of alloy compositions, key fatigue properties, and additional information influential to, or interrelated with, fatigue (e.g., material processing history, phase constitution, grain size, uniaxial tensile properties, and fatigue testing conditions), and an individual dataset, which makes up the original fatigue testing curve. Some representative individual datasets in each category are graphically visualized. The dataset is hosted in an open data repository, Materials Cloud.

Fatigue database of additively manufactured alloys

“…Journal articles, conference proceedings, and technical reports form a vast and continually growing corpus of unstructured information, which can be processed by state-of-the-art natural language processing (NLP), ML, and computer vision (CV) techniques. Progress has been witnessed in this direction, where databases for material synthesis recipes 24 and properties 25 – 27 were released.…”

Deformation Behavior of 3D‐Printed High‐Entropy Alloys: A Critical Review

“…The thermal/fluidic edge effects at the contact of molten pool and powder beds lead to near-surface defects, [207] which would degrade the fatigue performance of 3D-printed components. [208] Though several researchers have studied the cyclic plasticity of conventionally produced HEAs, [9,[209][210][211][212][213] the corresponding exploration of 3D-printed HEAs is relatively nascent and scarce in contemporary materials science. [214] Since the microstructure of the 3D-printed metals is primarily different from traditionally manufactured materials, [208] their fatigue properties pose a wide research gap with tremendous potential.…”

“…[6] According to this notion, as multiple metallic elements are mixed, the tendency of forming intermetallic compounds is suppressed by the increased configurational entropy, which ultimately lowers the Gibbs free energy to form thermodynamically stable solid solutions called "high-entropy alloys" (HEAs). [1] Since their inception, the HEAs have triumphed over almost all domains of mechanical properties, including strength-ductility synergy, [7,8] fatigue [9] and fracture resistance, [10,11] dynamic response to ballistic impact, [12] wear and tribological performance, [13][14][15] mechanical integrity at high [16] and cryogenic [17] temperatures, weldability, [18,19] radiation resistance, [20,21] corrosion and oxidation resistance, [22,23] etc. Consequently, the upcoming breakthroughs in this era's vitally crucial domains of nuclear energy, [24] automotive and aerospace are foreseeable through HEA design.…”

Fatigue database of complex metallic alloys

“…Data science is of crucial importance in the research of MGs and MPEAs for the vast design space compared to conventional alloys. Experimentally measured 36 , 38 , 39 and theoretically predicted 40 , 41 data reported in the literature and research reports are valuable sources to understand and improve the performance of alloys. Text mining, image data processing, and artificial intelligence 37 , 42 techniques are expected to offer insights into the CPMP relationship as demonstrated in our recent work on AM alloys 43 .…”